A Residual-Information-Based Criterion for Model Order Selection
β Scribed by Xiaojun Duan; Xiaoyong Du; Zhengming Wang
- Publisher
- Springer
- Year
- 2003
- Tongue
- English
- Weight
- 371 KB
- Volume
- 22
- Category
- Article
- ISSN
- 0278-081X
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π SIMILAR VOLUMES
We propose a consistent criterion for model order selection in the model identification phase of time series and regression, based on a weighted average of an asymptotically efficient selection criterion, AICC (bias-corrected Akaike information criterion) and a consistent selection criterion, BIC (A
The Akaike information criterion, AIC, is a widely known and extensively used tool for statistical model selection. AIC serves as an asymptotically unbiased estimator of a variant of Kullback's directed divergence between the true model and a ΓΏtted approximating model. The directed divergence is an